Investigation of Patterned Textures in Ball-on-Disk Lubricated Point Contacts

School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081, Chinae-mail: wangwzhong@bit.edu.cn

Shen Dian, Zhang Shengguang, Zhao Ziqiang

School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081, China

1Corresponding author.

Contributed by the Tribology Division of ASME for publication in the JOURNAL OF TRIBOLOGY. Manuscript received March 27, 2014; final manuscript received September 9, 2014; published online October 21, 2014. Assoc. Editor: Dong Zhu.

Abstract

The numerical simulations of surface textures in point-contact lubrication are conducted based on the unified Reynolds equation model. The textures are numerically produced on one of the interacting surfaces. The lubricant rheological parameters used in the simulations are calibrated by experiments. The numerical results show good agreements with those from experiments. The friction reduction mechanism is investigated by systemically analyzing the periodic change of friction coefficient of textures. It is illustrated that the transient friction coefficient is minimal when the dent moves to the front boundary edge of the Hertzian contact zone. A local film enhancement region will be formed on the trail of the dent within the Hertzian contact region. The results suggest that a bigger local film enhancement area will offer stronger film thickness enhancement as well as a lower friction coefficient. Different pattern distributions are also studied to find the optimal distribution of patterned textures, which not only achieves a lower friction coefficient, but also offers stronger film thickness enhancement; moreover, the optimal distribution is numerically proved to be applicable for a wide range of working conditions.

Optimal distribution of single-row textures and Profiles of film thickness and pressure: (a) Schematic plot for optimal distribution of single-row textures and (b) film thickness and pressure profiles along center line for the optimal distribution

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